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AWS Software / SaaS Global

WPS Software

Document Processing

However, implementing generative AI in office software presented several complex challenges. WPS Software needed to evaluate and select suitable language models, manage model accuracy by reducing hallucinations, and adapt prompts effectively to ensure high-quality user interactions.

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For knowledge extraction, WPS AI utilizes Claude 3 to help users analyze and interpret data, supporting informed decision-making within WPS Office.
Today, over 200 million overseas users benefit from WPS AI’s capabilities, including advanced spell check, text rewriting, and automated PowerPoint generation.
WPS Software reported a 30 percent increase in R&D efficiency as a result of generative AI on AWS, freeing resources to focus on further innovations in the WPS Office suite.
With Claude 3’s expansive context window, WPS AI performs precise content extraction, delivering accurate and professional results with minimal input.

Reported impact

Business outcome

WPS Software introduced advanced features for WPS AI, transforming user productivity and content accuracy. Previously limited to basic spell checks, WPS AI now provides AI-powered spell check, grammar correction, and document polishing. Key reported metrics include With Claude 3’s expansive context window, WPS AI performs precise content extraction, delivering accurate and professional results with minimal input.; WPS Software reported a 30 percent increase in R&D efficiency as a result of generative AI on AWS, freeing resources to focus on further innovations in the WPS Office suite.; Today, over 200 million overseas users benefit from WPS AI’s capabilities, including advanced spell check,

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement
  • Risk Reduction
  • Scalability
  • Speed to Market

Solution

WPS Software Accelerates Smart Office Innovation with Generative AI, Deploying AI Features in Just 2 Months WPS Software , a global provider of office productivity software, supports millions of users worldwide with its flagship product, WPS Office. Driven by its "All in AI" initiative, WPS Software launched WPS AI, an intelligent assistant embedded in WPS Office, designed to enhance smart office capabilities with features like advanced spell check, document polishing, and automated PowerPoint generation. WPS Software selected Amazon Web Services (AWS) for its robust, scalable infrastructure and diverse AI model options. By deploying WPS AI on AWS, WPS Software achieved a 30 percent increase in R&D efficiency and a 35 percent reduction in operational costs, delivering transformative AI-driven tools that enhance productivity and user experience across its global user base.

Data flow

Source data enters the WPS Software workflow through its application services, stored or indexed in Amazon ECR, Amazon S3, processed with Amazon EKS, Amazon Bedrock, Claude 3, and delivered through Amazon CloudFront.

Solution architecture

8 components · 4 layers
  1. Compute
    • Amazon EKS Runs containerized workloads and Kubernetes-based application services.
    • Amazon Bedrock Hosts the foundation models and inference APIs that power the generative AI features.
    • Claude 3 Serves as the primary large language model for generation or analysis tasks.
  2. Storage
    • Amazon ECR Stores and distributes container images for application workloads.
    • Amazon S3 Stores raw, intermediate, or curated files and datasets.
  3. Serving
    • Amazon CloudFront Caches and serves application content close to end users.
  4. Governance
    • AWS IAM Controls authentication and authorization across AWS resources.
    • Amazon CloudWatch Collects operational telemetry and monitoring signals from the workload.

Architecture clues

  • Amazon Bedrock provides WPS Software with a unified API for selecting and evaluating models, enabling WPS AI to rapidly test and deploy models suited to specific business needs.
  • This close collaboration enabled WPS Software to overcome deployment challenges and ensured the rapid, successful rollout of WPS AI, delivering a reliable, intelligent assistant that transforms productivity across office
  • Using Claude 3 as its underlying language model, WPS AI streamlines workflows and task management, assisting users in various aspects of content creation and enhancing user efficiency.
  • “Amazon Bedrock provides us with diverse models, making it easy to find options that align with our objectives.” In addition to Amazon Bedrock, core AWS services such as Amazon CloudFront Amazon Elastic Container Registr

Evidence from the source

For knowledge extraction, WPS AI utilizes Claude 3 to help users analyze and interpret data, supporting informed decision-making within WPS Office.
However, implementing generative AI in office software presented several complex challenges. WPS Software needed to evaluate and select suitable language models, manage model accuracy by reducing hallucinations, and adapt prompts effectivel
To advance its AI-driven strategy, WPS Software introduced WPS AI for international users, integrating it directly into WPS Office as a versatile AI assistant.
Today, over 200 million overseas users benefit from WPS AI’s capabilities, including advanced spell check, text rewriting, and automated PowerPoint generation.
WPS Software reported a 30 percent increase in R&D efficiency as a result of generative AI on AWS, freeing resources to focus on further innovations in the WPS Office suite.
With Claude 3’s expansive context window, WPS AI performs precise content extraction, delivering accurate and professional results with minimal input.
Transparency Evidence & methodology 95/100 reference value · 87% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value95/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    3 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    6 direct source quotes retained.
  • Date provenance8/10
    The publication date comes from publisher-controlled metadata.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. AWS

    WPS Software customer story

    First-party
    https://aws.amazon.com/solutions/case-studies/wps/
    Source type
    Vendor-published customer story
    Published
    Nov 21, 2024
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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